Aldi, Edeka & Co. – Consumer preferences and
store image
Aldi, Edeka & Co. – Konsumentenpräferenzen und Einkaufsstättenwahl
Alexander STAUS1
Summary
Store choice decisions in the food retailing industry have been widely
discussed in the literature. The importance of pricing, quality and
assortment is known, and the influence of socio-demographic variables
is small. In this paper, a mixed nested logit model is used to study the
relationship between specific attitudes of households and their store
choice for fruits and vegetables in Germany. Household attitudes are
about environment, freshness, organic food, prices and quality. An
implied image ranking of stores regarding these attitudes can be
established. The weekly farmers’ market has throughout a very high
implied image, while the discounters Penny, Plus and Aldi enjoy good
to average images. The supermarkets Edeka and Rewe get comparable
bad results.
Keywords: store choice, mixed nested logit, image, fruits and
vegetables
Zusammenfassung
Über die Einkaufsstättenwahl im Lebensmitteleinzelhandel wurde
bereits ausgedehnt diskutiert. Preise, Qualität und Sortiment spielen
dabei eine wichtige Rolle, während soziodemographische Variablen
eher unbedeutend für die Einkaufsstättenwahl sind. Ein „Mixed
Nested Logit Modell“ untersucht den Zusammenhang zwischen der
Einkaufsstättenwahl und bestimmten Einstellungsmerkmalen (Bio,
Frische, Umwelt, Preis und Qualität) von Konsumenten für Obst und
Gemüse in Deutschland. Ein implizites Image-Ranking bezüglich der
betrachteten Variablen kann erstellt werden. Wochenmärkte erhalten
Erschienen 2011 im Jahrbuch der Österreichischen Gesellschaft für Agrarökonomie,
Band 20(2): 13-22. On-line verfügbar: http://oega.boku.ac.at.
14
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durchweg ein sehr gutes implizites Image, während die Discounter
Penny, Plus und Aldi gute bis mittlere Bewertungen erhalten. Die
Supermärkte Edeka und Rewe schneiden unterdurchschnittlich ab.
Schlagworte: Einkaufsstättenwahl, Mixed Nested Logit, Image, Obst
und Gemüse
1. Introduction
Expenditures on food and soft drinks were 152 bn euros in Germany in
2008. The share of food expenditures in total expenses was about 11%,
which is nearly the lowest in a European comparison. In the EU-27, the
share was on average 19.4%. Expenditures for fruits and vegetables
(f&v) have increased from 16.3 bn in 1991 to 23 bn euros in 2008.
The food retailing sector in Germany is in heavy competition. Only a
few large retailers in Germany share the largest portion of the market.
The six companies Edeka, Rewe, Schwarz, Aldi, Metro and
Tengelmann share more than 75% of total revenues in the food market.
The companies use different stores and store types to sell their
groceries. A store type is generally characterized by stores, which have
similar attributes over a long time period. They can be classified by
four categories: 1. the amount of different products (full, part or
special), 2. general service (self-service), 3. service (personnel, location)
and 4. quality of products (SPECHT and FRITZ, 2005). Distinguished by
these four categories, four different main store types are established in
the food market: discounters, supermarkets, small and large
hypermarkets. For f&v, specialized stores like weekly farmers’ markets
can be added as a store type as they account for about 6% of all store
choices within f&v. The stores within a store type usually share many
similar characteristics, but nevertheless they are mostly at least a bit
different.
The consumers’ decision to buy groceries is based on a dynamic
decision behaviour of 1. determining whether there is a need to go
shopping or not, 2. deciding what purchases need to be made, and 3.
choosing a particular store (LESZCZYC et al., 2000). At the third decision,
choosing a particular store, first a specific store type is chosen and then
a specific store within this store type. The existing literature on store or
store type choice is huge. There are static models which consider one
time period and provide a snapshot of current consumer decisions.
Aldi, Edeka & Co. – Consumer preferences and store image
15
GONZÁLEZ-BENITO et al. (2005) and SOLGAARD and HANSEN (2003)
among others use a kind of logit model and conclude that price level,
assortment and distance are the most significant variables influencing
consumer choice of store type; quality and service have no notable
influence. On the other hand there are dynamic models which take the
sequence of choices into account. They usually include a loyalty factor.
Following BUCKLIN and LATTIN (1992) and LESZCZYC et al. (2000),
demographics have almost no influence on store-switching, but loyalty
is important and promotions increase the probability of visiting a store.
PAN and ZINKHAN (2006) obtain the following sequence of factors in
their meta-study: assortment, service, quality, location and price. The
sequence depends on the merchandise category studied or the method
used.
This paper analyzes store choices of households in the food market for
f&v. It considers specific consumer attitudes towards quality,
freshness, environment, organic food and prices, several sociodemographics and a loyalty factor. While the retailer determinants
have been analyzed extensively, there is up to now no research with
the focus on the explicit role of consumer attitudes towards store
choice. Analyzing these attitudes and the actual point of purchase
shows, which of these attitudes actually influence to which degree
store choice. It shows which store is preferred by e.g. quality
orientated, freshness orientated, organic food orientated, or priceconscious households. Assuming there is a true relation between these
choices, an implied image ranking can be established. That means it
can be shown that e.g. specific stores have a higher or lower implied
quality or price image. Suggestions can be given for improving the
implied image of specific stores.
2. Data and Model
The dataset is provided by the GFK GROUP (2009) and is based on their
ConsumerScan household panel dataset. The GfK records a
representative sample of more than 12,000 households. The aim of GfK
is the continuous collection of all purchases of these households, with
focus on fast moving consumer goods. 1,300 households with f&v
purchases between January and June 2006 are randomly selected for
estimation and a random sample of 700 households is taken for
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validation. The socio-demographics age, gender and income are
included in the model. The householder who is responsible for
shopping answers attitudes towards different themes, which influence
store choice. This paper considers attitudes about quality, freshness,
pricing, environment and organic food, to estimate store choice. These
attitudes can be split into two categories: (a) quality, freshness, pricing
and (b) environment, organic food. The variables of the first category
(a) are mostly included in past research, but determined by the
retailers. Instead of concluding, that quality, freshness and pricing,
determined by the researcher, are important, this study distinguishes
between the attitudes of households towards these variables. For
instance individuals can have a high-quality preference, a lowfreshness preference or do not care about pricing. These attitudes are
not captured by the according retailer determinants and need therefore
a closer examination, regarding that not all households have the same
preferences. Category (b)-variables were seldom considered yet. Store
types are likely associated with different characteristics of these
variables.
After the realization, whether there is a need to go shopping or not,
which is the very first decision, also the choice of the products is the
base for further decisions. In LESZCZYC et al. (2000), next comes the
choice of the store, similar to DILLER et al. (1997), who sees a strong
relation between the brand or product choice and the store choice.
KRAFFT and ALBERS (1996) say that the selected store type affects the
buying behaviour more directly than just the single store choice.
Following KRAFFT and ALBERS (1996), store type choice is, knowing
which products to buy, the second decision. GONZÁLEZ-BENITO et al.
(2005) support this result; they conclude that the consumers choose
first a specific store type and then a single store within this store type.
Accounting for this information, a mixed nested logit model (mixed
NL) is used to estimate store choice. The stores are nested within store
types, an individual i chooses a specific store, given his store type
choice. The mixed NL allows random taste variation, correlation in
unobserved factors over time and unrestricted substitution patterns
(TRAIN, 2003). Taste variation maybe also understood as
“heterogeneity”, where unobserved tastes influence the choices, and
these unobserved tastes are independent from past choices.
Aldi, Edeka & Co. – Consumer preferences and store image
17
The mixed NL is used with random coefficients for each grocery store
type and with fixed coefficients for all other variables. Random effects
are applied only to the intercepts for capturing heterogeneity through
not included variables. The log-likelihood function to estimate has no
closed-form expression due to the inclusion of random coefficients. The
multi-dimensional integral contains four dimensions and cannot be
solved analytically. To maximize the likelihood function of the mixed
NL the literature suggests numerical integration methods like adaptive
quadrature or simulation. The resulting estimator is called Maximum
Simulated Likelihood (MSL). In this paper 200 Halton sequences are
taken for every household to simulate the model. Halton sequences are
one of the most popular quasi-random types (HESS et al., 2003) and
were first introduced by HALTON (1960). Halton sequences ensure a
better coverage of the multi-dimensional area of integration than
random draws. With this better coverage, fewer draws need to be
taken than with pseudo-random numbers and this reduces
computational time. For discrete choice models TRAIN (2000) and BHAT
(2001) show, that 100 Halton draws provide better accuracy than 1,000
pseudo-random draws do.
Consumers facing the same set of alternatives and having the same
characteristics may make different choices. HECKMAN (1981)
introduced two possible explanations for this behaviour. The first
explanation is that past choices or experiences of consumers influence
directly current choices. Even if characteristics of the chosen alternative
or characteristics of the consumer change over time, the consumer
might choose always the same alternative. Consumers, who did not
experience this alternative in the past, with all characteristics being the
same, might behave differently on the current choice. HECKMAN (1981)
calls this “true state dependence”. Explanations for this behaviour may
be e.g. habit persistence or learning combined with risk aversion
(KEANE, 1997). Another explanation is that there are unobserved tastes,
which influence the choices and that these unobserved tastes are
independent from the past choice. An existing correlation over time
between the unobserved tastes seems for the researcher, as if past
choices influence current choices. In this case there is “spurious state
dependence”, also termed as “heterogeneity”. To ignore either
heterogeneity or true state dependence can lead to misspecification and
therefore to biased estimators. The fact, whether there is spurious or
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18
true state dependence in a specific market, is important for decisions of
firms about changing choice variables directly or indirectly. The used
mixed NL with random intercepts allows for heterogeneity.
Unobserved tastes are absorbed by the random intercept. But how can
true state dependence be modelled? True state dependence is often
linked to the term “loyalty” and there are several ways to introduce a
loyalty factor. In this paper, a dummy variable which is 1 if the
previous choice is the same choice as the current choice is used, like
e.g. in GROVER and SRINIVASAN (1987), KRISHNAMURTHI and RAJ (1991),
BUCKLIN and LATTIN (1992), GOLDFARB (2006), RAMADURAI and
SRINIVASAN (2006).
To identify the model, the discounter Aldi is taken as the base category,
so all coefficients for that choice are normalized to zero. This leads all
coefficients to interpret relative to Aldi. Table 1 shows the included
retailers and the according distributive channels with their share of
choices in the dataset for f&v.
Tab. 1: Retailers and their distributive channels share of choices (in %)
Edeka
Rewe
Schwarz
Tengelmann
Discounters
Netto
Penny
Lidl
Plus
(4.8%)
(5.7%)
(9.5%)
(3.8%)
Supermarkets
Edeka
(3.9%)
Other
Aldi
(18.5%)
Norma
(3.8%)
Rewe
(3.5%)
Large
Kaufland
hypermarkets
(9.4%)
Specialized
weekly farmers’ market
stores
(6.2%)
Note: The retailers and their listed distributive channels are based on data from
June 30th, 2006. Only stores with a market share of more than 3% are included.
Source: Own illustration
3. Results
Three different models are estimated: 1. The basic model, where only
the household attitudes are used to explain consumers’ choice.
Additionally a random constant is estimated allowing for an intrinsic
preference for one or another store type. 2. The dummy loyalty model
Aldi, Edeka & Co. – Consumer preferences and store image
19
extends the basic model by a loyalty variable. Loyalty is represented by
a dummy variable, which is 1 if the previous choice is the same choice
as the current choice. 3. The socio-demographic model, which extends
the basic model by the three variables age, gender and income.
Correct predictions within the validation sample are between 11.3 and
25.8 percentage points superior to the chance criterion. The chance
criterion is simply the share of the most chosen store. The estimated
standard deviations of the random coefficients are all highly
significant. Heterogeneity over households is present and nearly all
random coefficients are significant. The influence of the sociodemographics is small. The loyalty dummies are significant for most
stores and represent mostly the share of purchasing occasions.
The 27% of consumers who care about the environment prefer Rewe
and weekly farmers’ markets. Nearly all other stores are less preferred
compared to Aldi. The within-variance regarding environmental
characteristics for f&v is supported by the result that foreign farmers’
markets are less preferred than some discounters by consumers who
care about the environment, and a standard weekly farmers’ market is
more preferred. Within discounters, Aldi is the ruling store. Penny,
Plus, Netto and Norma are generally less preferred with no significant
difference within these stores.
The specialized stores (foreign and weekly farmers’ market) are the
most favored stores for f&v by consumers who care about freshness.
Also the discounters Plus and Penny are preferred compared to Edeka
or Rewe and the other discounters. The implied freshness image of the
supermarkets is the lowest over all stores. The discounters score on
average quite well, but Aldi is not generally the most preferred store
within the discounters. The implicit freshness image ranking, starting
with the highest image, is: weekly farmers’ or foreign farmers’ market
or Plus, Penny, Aldi, Lidl, Netto, Edeka or Rewe.
Specialized stores are the most preferred stores by the 26% of
households in the dataset who like organic food. The supermarkets get
the worst results and Plus and Netto are the preferred discounters. The
implicit organic food image ranking, starting with the highest image,
is: weekly farmers’ or foreign farmers’ market, Kaufland or Penny or
Plus, Aldi, Edeka or Rewe.
The store types can be classified into different price strategies:
Discounters offer every-day-low-pricing (EDLP), supermarkets offer
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high-low pricing (HiLo), small and large hypermarkets offer hybrid
pricing. Specialized stores offer prices between hybrid and high. The
associated price order beginning with the lowest priced store type is
discounter, large hypermarket, supermarket, small hypermarket and
specialized store. It is assumed that price- and very price-conscious
consumers prefer store types with a lower price image. Mainly the
specialized stores are avoided and the large hypermarket Kaufland is
preferred compared to discounters. There are two explanations why
Kaufland is preferred to the discounters. First, consumers perceive
large hypermarkets in average as really “cheaper” than discounters.
Second, the hybrid pricing of large hypermarkets keep cherry pickers
going to this store type. The huge assortment gives enough
opportunities for consumers to find cheaper groceries than in
discounters. Within the discounters, Aldi is the preferred discounter,
means Aldi has the lowest implied price image of all discounters.
One way to signal quality is the use of prices as MILGROM and ROBERTS
(1986) state. High prices signal high quality, and low prices signal low
quality. The discounters Norma and Aldi are the least choice for f&v by
quality orientated consumers. Lidl and Netto have a higher implied
quality image. The specialized stores enjoy the highest implied image
for f&v and enjoy therefore the highest confidence for this quality
sensitive grocery. The implicit quality image ranking, starting with the
highest image, is: weekly farmers’ or foreign farmers’ market, Edeka,
Netto or Lidl, Aldi, Norma. Table 2 shows the implied image ranking
of the attitude variables.
4. Discussion
Foreign and weekly farmers’ markets enjoy the highest implied
freshness, organic food and quality image. Foreign farmers’ markets
are rather negatively associated within the environment attitude.
Nevertheless, the very good implied images come hand in hand with
the highest implied price image. The supermarkets Edeka and Rewe
get comparable bad results for freshness and organic food, while the
discounters Plus and Penny score quite well in these two categories.
Aldi gets average results in most categories.
Several issues have to be considered. The households reported their
purchases by their own. Due to the self-observation one can expect
Aldi, Edeka & Co. – Consumer preferences and store image
21
some changes in behaviour and therefore some bias in the estimation
results. The intention to capture true loyalty by a dummy variable is
rather unlikely. It can just represent, that visiting one store at one time,
increases the probability to visit the same store next time. True loyalty
cannot be captured by just the revealed point of purchase without
further information of the consumer.
Tab. 2: The implied image ranking of the attitude variables
IIR*
Organic
Freshness
Environment
Pricing
weekly
weekly
weekly
weekly
1.
farmers’
farmers’/Plus farmers’/Rewe farmers’
Kaufland/
Penny/
2.
Penny
Aldi
Penny/Plus
Norma
3.
Aldi
Aldi
Netto
Aldi
4.
5.
Edeka/Rewe
Lidl
Netto
Penny
Kaufland/
Norma/Plus
Kaufland
Quality
weekly
farmers’
Edeka
Lidl/
Netto
Aldi
Norma
Edeka / Rewe
6.
* IIR = Implied Image Ranking
Source: Own illustration
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Affiliation
Dr. Alexander Staus
Universität Hohenheim
Schloss Hohenheim, 70593 Stuttgart, Germany
Tel.: +49 711 459 24304
eMail: alexander.staus@uni-hohenheim.de